This paper presents an unsupervised learning approach to disambiguate various relations between name entities by use of various lexical and syntactic features from the contexts. I...
Jinxiu Chen, Dong-Hong Ji, Chew Lim Tan, Zheng-Yu ...
Support vector clustering transforms the data into a high dimensional feature space, where a decision function is computed. In the original space, the function outlines the bounda...
Background: Microarray gene expression data are often analyzed together with corresponding physiological response and clinical metadata of biological subjects, e.g. patients'...
High dimensionality remains a significant challenge for document clustering. Recent approaches used frequent itemsets and closed frequent itemsets to reduce dimensionality, and to...
In this paper we describe an interdisciplinary collaboration between researchers in machine learning and oceanography. The collaboration was formed to study the problem of open oc...
Joshua M. Lewis, Pincelli M. Hull, Kilian Q. Weinb...